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At least 505 records · Page 28

Using AVIRIS for in-flight calibration of the spectral shifts of SPOT-HRV and of AVHRR?

The response of a satellite sensor varies during its lifetime; internal calibration devices can be used to follow the sensor degradation or in-flight calibrations are conducted from estimates of the radiance at satellite level for well predictable situations. Changes in gain are evaluated assuming that the spectral response of the sensor is stable with time; i.e., that the filter response as well as the optics or the electronics are not modified since the prelaunch determinations. Nevertheless, there is some evidence that the SPOT interferometer filters are affected by outgassing effects during the launch. Tests in vacuum chambers indicated a narrowing of the filters with a shift of the upper side towards the blue of about 10 nm which is more over consistant with the loss of gain observed during the launch. Also, during the lifetime of SPOT, the relationship between the loss of sensitivity and the filter bandwidth may correspond to this effect. On the other hand, the inconsistancy of the NOAA7 calibration between two methods (desert and ocean) having a different spectral sensitivity may indicate a spectral problem with a shift of the central wavelength of -20 nm. The basic idea here is to take advantage of the good spectral definition of AVIRIS to monitor these potential spectral degradations with an experimental opportunity provided by a field campaign held in La Crau (S.E. of France) in June 1991 which associated ground-based measurements and AVIRIS, SPOT2, NOAA-11 overpasses over both the calibration site of La Crau and an agricultural area.

Willart-Soufflet, Veronique↗

A model for excess Johnson noise in superconducting transition-edge sensors

Transition-edge sensors (TESs) are two-dimensional superconducting films utilized as highly sensitive detectors of energy or power. These detectors are voltage biased in the superconducting-normal transition where the film resistance is both finite and a strong function of temperature. Unfortunately, the amount of electrical noise observed in TESs exceeds the predictions of existing noise theories. We describe a possible mechanism for the unexplained excess noise, which we term “mixed-down noise.” The source is Johnson noise, which is mixed down to low frequencies by Josephson oscillations in devices with a nonlinear current–voltage relationship. We derive an expression for the power spectral density of this noise and show that its predictions agree with measured data.

Wessels, Abigail (ORCID:0000000173918339)↗

Predicted continuum spectra of type II supernovae - LTE results

The continuum spectral energy distribution of the flux emerging from type II supernovae is calculated from quasi-static radiative transfer through a power-law density gradient, assuming radiative equilibrium and LTE. It is found that the Balmer jump disappears at high effective temperatures and low densities, while the spectrum resembles that of a dilute blackbody but is flatter with a sharper cutoff at the short-wavelength end. A significant UV excess is found in all models calculated. The calculation should be considered exploratory because of significant effects which are anticipated to arise from departure from LTE.

Shaviv, G.↗

Validation of High Speed Earth Atmospheric Entry Radiative Heating from 9.5 to 15.5 km/s

This paper presents an overview of the analysis and measurements of equilibrium radiation obtained in the NASA Ames Research Center's Electric Arc Shock Tube (EAST) facility as a part of recent testing aimed at reaching shock velocities up to 15.5 km/s. The goal of these experiments was to measure the level of radiation encountered during high speed Earth entry conditions, such as would be relevant for an asteroid, inter-planetary or lunar return mission. These experiments provide the first spectrally and spatially resolved data for high speed Earth entry and cover conditions ranging from 9.5 to 15.5 km/s at 13.3 and 26.6 Pa (0.1 and 0.2 Torr). The present analysis endeavors to provide a validation of shock tube radiation measurements and simulations at high speed conditions. A comprehensive comparison between the spectrally resolved absolute equilibrium radiance measured in EAST and the predictive tools, NEQAIR and HARA, is presented. In order to provide a more accurate representation of the agreement between the experimental and simulation results, the integrated value of radiance has been compared across four spectral regions (VUV, UV/Vis, Vis/NIR and IR) as a function of velocity. Results have generally shown excellent agreement between the two codes and EAST data for the Vis through IR spectral regions, however, discrepancies have been identified in the VUV and parts of the UV spectral regions. As a result of the analysis presented in this paper, an updated parametric uncertainty for high speed radiation in air has been evaluated to be [9.0%, -6.3%]. Furthermore, due to the nature of the radiating environment at these high shock speeds, initial calculations aimed at modeling phenomena that become more significant with increasing shock speed have been performed. These phenomena include analyzing the radiating species emitting ahead of the shock and the increased significance of radiative cooling mechanisms.

Equilibrium↗

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Shen, Samuel S. P.↗

Symplectic machine learning model for fast simulation of space-charge effects

Symplectic simulation of space-charge effects is crucial for the design and operation of high-intensity particle accelerators. Traditional methods for simulating these effects are often computationally expensive, resulting in significant overhead. In this work, we introduce a generative model based on a U-Net architecture within a generative adversarial network framework to efficiently simulate space-charge effects. The model is trained to predict the transverse multiparticle space-charge Hamiltonian, which can be physically computed using a gridless spectral method. The one-step symplectic transverse transfer map for the particles is then obtained by differentiating the predicted Hamiltonian. Benchmarking results demonstrate that this generative model achieves an order of magnitude higher computational efficiency compared to the spectral method, providing a highly efficient alternative for simulating space-charge effects with a large number of particles. By maintaining symplecticity, the model effectively preserves the phase-space structure and mitigates nonphysical errors in long-term simulations. This model has been integrated into jutrack, a novel autodifferentiable accelerator modeling code developed in the julia programming language.

Beam code development & simulation techniques↗

The use of satellite data in understanding and predicting convective and large-scale dynamical processes

A two-layer truncated baroclinic spectral model was developed to study the long-term evolution of disturbances to a baroclinically unstable mean flow. Topography and crudely-parameterized radiative processes were accounted for. As a result of Robert Schlaak's discovery of the underlying barotropic nature of the index oscillation as well as reviewers suggestions about the original manuscript, the model has been revised to allow for barotropic as well as baroclinic wave-mean flow interactions. The form-drag exerted by the topography on the barotropic part of the mean flow is larger than on the baroclinic part and thus researchers anticipate significant changes from the original calculations on the index oscillation when it is strongly modulated by topography. Researchers believe that since the index oscillation accounts for a significant portion of atmospheric temporal variance, the long term predictability could be improved if reliable forecasts of the index oscillation were available. Two spectral models of the index oscillation, one barotropic and the other baroclinic, have been developed. The latter allows for moisture, radiation, land-sea temperature countrasts, and energy exchanges with the underlying surface.

Dutton, J. A.↗

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

An aeroacoustic test was conducted at NASA Glenn Research Center on an integrated propulsion system designed to meet noise regulations of ICAO Chapter 4 with 10EPNdB cumulative margin. The test had two objectives: to demonstrate that the aircraft design did meet the noise goal, and to validate the acoustic design tools used in the design. Variations in the propulsion system design and its installation were tested and the results compared against predictions. Far-field arrays of microphones measured the acoustic spectral directivity, which was transformed to full scale as noise certification levels. Phased array measurements confirmed that the shielding of the installation model adequately simulated the full aircraft and provided data for validating RANS-based noise prediction tools. Particle image velocimetry confirmed that the flow field around the nozzle on the jet rig mimicked that of the full aircraft and produced flow data to validate the RANS solutions used in the noise predictions. The far-field acoustic measurements confirmed the empirical predictions for the noise. Results provided here detail the steps taken to ensure accuracy of the measurements and give insights into the physics of exhaust noise from installed propulsion systems in future supersonic vehicles.

aeroacousti↗

Aeroacoustic Validation of Installed Low Noise Propulsion for NASA's N+2 Supersonic Airliner

An aeroacoustic test was conducted at NASA Glenn Research Center on an integrated propulsion system designed to meet noise regulations of ICAO Chapter 4 with 10EPNdB cumulative margin. The test had two objectives: to demonstrate that the aircraft design did meet the noise goal, and to validate the acoustic design tools used in the design. Variations in the propulsion system design and its installation were tested and the results compared against predictions. Far-field arrays of microphones measured the acoustic spectral directivity, which was transformed to full scale as noise certification levels. Phased array measurements confirmed that the shielding of the installation model adequately simulated the full aircraft and provided data for validating RANS-based noise prediction tools. Particle image velocimetry confirmed that the flow field around the nozzle on the jet rig mimicked that of the full aircraft and produced flow data to validate the RANS solutions used in the noise predictions. The far-field acoustic measurements confirmed the empirical predictions for the noise. Results provided here detail the steps taken to ensure accuracy of the measurements and give insights into the physics of exhaust noise from installed propulsion systems in future supersonic vehicles.

supersonic↗

Applying Two-Dimensional Correlation Spectroscopy and Principal Component Analysis to Understand How Temperature Affects the Neptunium(V) Absorption Spectrum

The visible-near infrared (Vis-NIR) electronic absorption spectrum of neptunium(V) (NpO 2 + ) comprises numerous f-f electronic transitions with mostly undocumented temperature dependencies. The effect of temperature on the absorption spectrum of the pentavalent neptunyl dioxocation (NpO 2 + ) is an important factor to consider with spectrophotometric applications but has often been overlooked. Optical Vis-NIR absorption spectra (400–1700 nm) of Np(V) (0.017–0.89 M) in 1 M nitric acid were evaluated with varying temperatures (T = 10–80 °C). The intensity, position, and overall shape of the bands were sensitive to interactions with the solvent and coordination environment. Numerous temperature-induced isosbestic points were identified resulting from dynamic, overlapping peak shifts. Spectral variations were characterized using principal component analysis (PCA) and 2D correlation spectroscopy (COS). 2D-COS revealed that the absorption band near 1095 nm likely consists of two bands centered near 1087 and 1096 nm, which cannot be explained by current computational methods. 2D-COS analysis also provided an unambiguous assignment of unresolved peaks in the visible region for comparison with computational predictions. PCA was used to identify nonlinearity in the spectral response at elevated Np(V) concentrations ≥ 0.5 M. This unique experimental data and interpretation will foster a deeper understanding of the absorption spectra for complex actinyl ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design of sidewall treatment of cabin noise control of a twin engine turboprop aircraft

An analytical procedure was used to predict the noise transmission into the cabin of a twin engine general aviation aircraft. This model was then used to optimize the interior A weighted noise levels to an average value of about 85 dBA. The surface pressure noise spectral levels were selected utilizing experimental flight data and empirical predictions. The add on treatments considered in this optimization study include aluminum honeycomb panels, constrained layer damping tape, porous acoustic blankets, acoustic foams, septum barriers and limp trim panels which are isolated from the vibration of the main sidewall structure. To reduce the average noise level in the cabin from about 102 kBA (baseline) to 85 dBA (optimized), the added weight of the noise control treatment is about 2% of the total gross takeoff weight of the aircraft.

Vaicaitis, R.↗

Theoretical calculations on the electron absorption spectra of selected Polycyclic Aromatic Hydrocarbons (PAH) and derivatives

As a theoretical component of the joint effort with the laboratory of Dr. Lou Allamandola to search for potential candidates for interstellar organic carbon compound that are responsible for the visible diffuse interstellar absorption bands (DIB's), quantum mechanical calculations were performed on the electron absorption spectra of selected polycyclic aromatic hydrocarbons (PAH) and derivatives. In the completed project, 15 different species of naphthalene, its hydrogen abstraction and addition derivatives, and corresponding cations and anions were studied. Using semiempirical quantum mechanical method INDO/S, the ground electronic state of each species was evaluated with restricted Hartree-Fock scheme and limited configuration interaction. The lowest energy spin state for each species was used for electron absorption calculations. Results indicate that these calculations are accurate enough to reproduce the spectra of naphthalene cation and anion observed in neon matrix. The spectral pattern of the hydrogen abstraction and addition derivatives predicted based on these results indicate that the electron configuration of the pi orbitals of these species is the dominant determinant. A combined list of 19 absorptions calculated from 4500 A to 10,400 A were compiled and suggested as potential candidates that are relevant for the DIB's absorptions. Continued studies on pyrene and derivatives revealed the ground state symmetries and multiplicities of its neutral, anionic, and cationic species. Spectral calculations show that the cation (B(sub 3g)-2) and the anion (A(sub u)-2) are more likely to have low energy absorptions in the regions between 10 kK and 20 kK, similar to naphthalene. These absorptions, together with those to be determined from the hydrogen abstraction and addition derivatives of pyrene, can be used to provide additional candidates and suggest experimental work in the search for interstellar compounds that are responsible for DIB's.

Du, Ping↗

On the use of the noncentral chi-square density function for the distribution of helicopter spectral estimates

A probability density function for the variability of ensemble averaged spectral estimates from helicopter acoustic signals in Gaussian background noise was evaluated. Numerical methods for calculating the density function and for determining confidence limits were explored. Density functions were predicted for both synthesized and experimental data and compared with observed spectral estimate variability.

Garber, Donald P.↗

Effects of micrometer-scale surface roughness on thermal infrared emittance spectra of silica glass

Surface roughness is known to decrease thermal infrared (TIR) absorption band intensity, but studies of the effect on geologically relevant samples are relatively limited. To determine the effect of surface roughness (with features smaller than ~2/3 of the wavelength) on TIR spectra, we investigated two glass compositions with prepared roughened surfaces: (1) high purity fused silica and (2) soda-lime glass (73 wt% SiO$_2$). We roughened the surfaces of the glasses by sandblasting and polishing with grit paper. The surfaces were characterized with scanning electron microscopy and stylus profilometry. We then analyzed the roughened glasses with TIR emittance spectroscopy. Micrometer-scale roughness causes a decrease in TIR absorption band intensity, relative to a specular surface. No significant changes in band shape or shifts in wavelength were detected. As roughness increases, empirical results show a logarithmic decrease in TIR absorption band intensity. The logarithmic trends of the two glass compositions are different; empirical roughness calibrations do not translate across different compositions. A linear, least-squares spectral deconvolution using two endmembers, specular and blackbody, predicts model spectra of roughened glass surfaces with relatively low error. This is of consequence to orbital TIR measurements of poorly constrained targets, such as the martian surface, because micrometer-scale roughness is adequately modeled by the addition of a blackbody spectrum to the deconvolution endmember matrix.

36 MATERIALS SCIENCE↗

Cross-scale sensing of field-level crop residue cover: Integrating field photos, airborne hyperspectral imaging, and satellite data

Conservation tillage practices can bring benefits to agricultural sustainability. Accurate spatial and temporal resolved information of field-scale crop residue cover, which reflects tillage intensity, is highly valuable for evaluating the outcomes of government conservation programs and voluntary ecosystem service markets, as well as facilitating agroecosystem modeling to quantify cropland biogeochemical processes. Remote sensing has the potential to cost-effectively detect crop residue cover, however, existing regional-scale studies were limited by insufficient ground truth data, scale mismatch between coarse satellite pixels and ground data, and the lack of key spectral data for detecting crop residues. Therefore, this study developed an innovative cross-sensing framework to integrate proximal sensing, airborne hyperspectral imaging, and satellite Earth Observation through deep learning to quantify field-level crop residue cover fractions at the regional scale. Specifically, we have collected intensive ground orthographic photos and conducted airborne hyperspectral surveys at corn and soybean fields of Champaign and nearby counties in Illinois, the heartland of the U.S. Corn Belt. Through semi-automatic labeling aided by ResNet-50 and superpixel image segmentation, we obtained 6719 records of ground residue fractions. With these ground data, we developed the 1-dimensional convolution neural network (CNN) model using airborne hyperspectral reflectance, which has 0.5m spatial resolution and 3–5 nm spectral resolution from 400 to 2400 nm, to predict residue fractions. By applying the CNN model to airborne pixels, we augmented “ground truth” data of crop residues and further combined them with Harmonized Landsat and Sentinel-2 (HLS) satellite data to quantify regional residue fractions at 30 m resolution. Results show that airborne hyperspectral imagery with CNN can accurately detect residue fractions (R 2 = 0.82, relative RMSE = 11.73%) to effectively generate quasi “ground truth” data to support satellite upscaling to all fields. With independent ground data for testing, we found that the ground-airborne-satellite integrative framework achieved better predictions in estimating crop residue cover (R 2 = 0.67, relative RMSE = 17.53%) than the conventional ground-satellite upscaling (R 2 = 0.22, relative RMSE = 32.09%). Here we also found that the shortwave infrared wavelengths, particularly 2100–2300 nm, are vital for predicting crop residue cover. Sentinel-2 and Landsat-8 data have a comparable capability to track residue fractions due to similar shortwave infrared wavelengths. This study highlights the high accuracy of hyperspectral imaging to detect agroecosystem tillage management practices and the advantages of cross-scale sensing to cost-effectively integrate multi-source data to quantify field-level agroecosystem variables across scales.

60 APPLIED LIFE SCIENCES↗

Robust Machine Learning Inference from X-ray Absorption Near Edge Spectra through Featurization

X-ray absorption spectroscopy (XAS) is a commonly employed technique for characterizing functional materials. In particular, X-ray absorption near edge spectra (XANES) encode local coordination and electronic information, and machine learning approaches to extract this information are of significant interest. To date, most ML approaches for XANES have primarily focused on using the raw spectral intensities as input, overlooking the potential benefits of incorporating spectral transformations and dimensionality reduction techniques into ML predictions. Here, in this work, we focused on systematically comparing the impact of different featurization methods on the performance of ML models for XAS analysis. We evaluated the classification and regression capabilities of these models on computed data sets and validated their performance on previously unseen experimental data sets. Our analysis revealed an intriguing discovery: the cumulative distribution function feature achieves both high prediction accuracy and exceptional transferability. This remarkably robust performance can be attributed to its tolerance to horizontal shifts in the spectra, which is crucial when validating models using experimental data. While this work exclusively focuses on XANES analysis, we anticipate that the methodology presented here will hold promise as a versatile asset to the broader spectroscopy community.

36 MATERIALS SCIENCE↗

Transforming the $v$ World: A New Multivariate Transformer Energy Estimator for NOvA

The NOvA Transformer Energy Estimator (Transformer_EE) is a universal machine learning tool currently used to infer the incoming beam neutrino energy and the outgoing lepton energy in both near andfar detectors. It uses a unique, highly flexible framework for simultaneous multivariate prediction that supports many possible loss functions. A spectral reweighting and flattening scheme lessens training bias. A feature noising subroutine enables adversarial-like training, mitigating sensitivities to certain systematic effects at marginal resolution loss at inference time. The state of the Transformer_EE will be reviewed, and its robustness with respect to several NOvA Near and Far Detector systematics highlighted.

Tong, Leon [Minnesota U.] (ORCID:0000000231625965)↗

Airframe noise - The next aircraft noise barrier

Progress in quieting the commercial aviation fleet has been achieved by reducing the noise generated by jet engines. Recent tests have indicated that noise produced by airflow over aircraft surfaces (lifting surfaces, landing gear, flaps, and cavities) is only 8 to 10 EPNdB below certification requirements for current aircraft and will likely be a design consideration for aircraft of the future as engines become still quieter. This paper reviews the state of the art for understanding, predicting, and control of airframe noise. Levels and spectral content of the noise, correlation with important variables, and noise generation mechansims are discussed. The noise floors for future aircraft, the direction of research projects, and likely impact of this new technology on aircraft design are indicated.

Morgan, H. G.↗